Beginner score
48/100
Competition workspace
适合有 Linux/openEuler 环境经验、能够从源码适配和构建 PyTorch 2.x 及其生态工具链的开发者或团队。还需要能在 EUR 中处理软件及依赖构建，并将主流 AI 模型实际部署到 openEuler 上运行。
Suggested next step
Decide whether this contest fits your current stage before you sink time into the leaderboard.
Beginner score
48/100
Learning value
60/100
Estimated effort
12-40 hours
Metric
Official scoring is published on the Op…
适合有 Linux/openEuler 环境经验、能够从源码适配和构建 PyTorch 2.x 及其生态工具链的开发者或团队。还需要能在 EUR 中处理软件及依赖构建，并将主流 AI 模型实际部署到 openEuler 上运行。
If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.
openEuler 系统使用
PyTorch 2.x 构建与移植
Linux 软件包构建
AtomGit 与 Git
EUR 软件仓使用
AI 模型部署与推理
The real friction is usually not library usage. It is validation, time allocation, and task framing.
核心难点不是单纯训练模型，而是完成从框架移植、软件包和依赖构建，到 EUR 安装部署及模型推理验证的一整套发行版适配流程。作品还需在 AtomGit 提交构建脚本，优胜方案将合入 openEuler 社区代码主干，因此工程可复现性和社区集成质量会是主要工作量。
This guide is the best pre-read if you want a cleaner start instead of trial-and-error.
How to learn feature engineering, validation, and competition workflow without heavy hardware.
No GPU? Pick Competitions That Still Teach You Good HabitsUse these fields to make a quick decision before you dive deeper.
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Rules, files, submission details, and the live deadline still come from the official page.
These competitions share a similar domain or difficulty level.
Separate what is confirmed from what still needs review. Official rules and deadlines win — report anything that looks wrong.
Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.
reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.